AN IMMUNE SMALL WORLD ALGORITHM FOR MOTION PLANNING OF THE MOBILE MANIPULATOR

Naijian Chen, Guoping Li, Fangzhen Song, Xuan Sun, and Changsheng Ai

Keywords

Motion planning, mobile manipulator, immune, small world

Abstract

A novel, generic method for motion planning of the mobile manipulator is developed on the small world phenomenon and the artificial immune system paradigms in this paper. Based on manipulability and the configuration changing index of the mobile manipulator, an optimization criterion is designed to solve the difficulties of the redundant degree of freedoms in trajectory-generating, and an artificial immune small world algorithm is proposed to motion planning online. The problem is formulated with the total motion cost of configuration changes in the mobile platform and the manipulator to achieve a desired trajectory. The primary optimization variables are the heading angle, the position of the platform and rotating angles of manipulator joints. In the proposed algorithm, the clustering and the long-range shortcuts of small world phenomenon mutation are introduced to improve the randomness of somatic cell hypermutation, and the combination of clone deleting and small world eﬀect has advantages in genetic diversity within populations. Simulation results show that the optimization method is validated for multi-modal function and point to point motion planning of the mobile manipulator.